Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, China
A series of urban law enforcement events involving city inspectors dispatched by the city management department can reflect some problems in smart city management, such as illegal advertising and unlicensed street operation. In this paper, we propose a model for the allocation of city inspectors and...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/11/3/171 |
| _version_ | 1797471068689006592 |
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| author | Yirui Jiang Hongwei Li Binbin Feng Zekang Wu Shan Zhao Zhaohui Wang |
| author_facet | Yirui Jiang Hongwei Li Binbin Feng Zekang Wu Shan Zhao Zhaohui Wang |
| author_sort | Yirui Jiang |
| collection | DOAJ |
| description | A series of urban law enforcement events involving city inspectors dispatched by the city management department can reflect some problems in smart city management, such as illegal advertising and unlicensed street operation. In this paper, we propose a model for the allocation of city inspectors and the optimization of patrol paths. The objective is to minimize the average response time and the number of inspectors. We also develop a priority-patrol-and-multiobjective genetic algorithm (DP-MOGA) to classify patrol segments according to the frequency of events and develop an improved genetic algorithm to achieve the aforementioned objective. We conduct numerical experiments using patrol data obtained from city inspectors in Zhengzhou, China, to clearly show that the proposed algorithm generates reasonable routes that reduce the average response time of events and the number of patrol inspectors. Furthermore, we test the algorithm for three different time scenarios (roads with different average numbers of events) and demonstrate the efficiency of the algorithm. The experimental results show that our proposed algorithm is more stable and efficient than other existing algorithms. |
| first_indexed | 2024-03-09T19:44:21Z |
| format | Article |
| id | doaj.art-5ba1182daaab43a98697536551d340a9 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-09T19:44:21Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-5ba1182daaab43a98697536551d340a92023-11-24T01:28:17ZengMDPI AGISPRS International Journal of Geo-Information2220-99642022-03-0111317110.3390/ijgi11030171Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, ChinaYirui Jiang0Hongwei Li1Binbin Feng2Zekang Wu3Shan Zhao4Zhaohui Wang5School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou 450001, ChinaSchool of Geoscience and Technology, Zhengzhou University, Zhengzhou 450001, ChinaSchool of Geoscience and Technology, Zhengzhou University, Zhengzhou 450001, ChinaSchool of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou 450001, ChinaSchool of Geoscience and Technology, Zhengzhou University, Zhengzhou 450001, ChinaDigital Urban Management Supervision Center of Zhengzhou, Zhengzhou University, Zhengzhou 450001, ChinaA series of urban law enforcement events involving city inspectors dispatched by the city management department can reflect some problems in smart city management, such as illegal advertising and unlicensed street operation. In this paper, we propose a model for the allocation of city inspectors and the optimization of patrol paths. The objective is to minimize the average response time and the number of inspectors. We also develop a priority-patrol-and-multiobjective genetic algorithm (DP-MOGA) to classify patrol segments according to the frequency of events and develop an improved genetic algorithm to achieve the aforementioned objective. We conduct numerical experiments using patrol data obtained from city inspectors in Zhengzhou, China, to clearly show that the proposed algorithm generates reasonable routes that reduce the average response time of events and the number of patrol inspectors. Furthermore, we test the algorithm for three different time scenarios (roads with different average numbers of events) and demonstrate the efficiency of the algorithm. The experimental results show that our proposed algorithm is more stable and efficient than other existing algorithms.https://www.mdpi.com/2220-9964/11/3/171patrol routing optimizationsmart city managementroad segment classificationgenetic algorithm |
| spellingShingle | Yirui Jiang Hongwei Li Binbin Feng Zekang Wu Shan Zhao Zhaohui Wang Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, China ISPRS International Journal of Geo-Information patrol routing optimization smart city management road segment classification genetic algorithm |
| title | Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, China |
| title_full | Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, China |
| title_fullStr | Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, China |
| title_full_unstemmed | Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, China |
| title_short | Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, China |
| title_sort | street patrol routing optimization in smart city management based on genetic algorithm a case in zhengzhou china |
| topic | patrol routing optimization smart city management road segment classification genetic algorithm |
| url | https://www.mdpi.com/2220-9964/11/3/171 |
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